Abstract
Researchers such as sociologists create visualizations of multivariate node-link diagrams to present findings about the relationships in communities. Unfortunately, such visualizations can inadvertently expose the ostensibly private identities of the persons that make up the dataset. By purposely violating graph readability metrics for a small region of the graph, we conjecture that local, exposed privacy leaks may be perceptually masked from easy recognition. In particular, we consider three commonly known metrics∗edge crossing, node clustering, and node-edge overlapping∗as a strategy to hide leaks. We evaluate the effectiveness of violating these metrics by conducting a user study that measures subject performance at visually searching for and identifying a privacy leak. Results show that when more masking operations are applied, participants needed more time to locate the privacy leak, though exhaustive, brute force search can eventually find it. We suggest future directions on how perceptual masking can be a viable strategy, primarily where modifying the underlying network structure is unfeasible.
| Original language | English (US) |
|---|---|
| Title of host publication | 2018 IEEE Symposium on Visualization for Cyber Security, VizSec 2018 |
| Editors | Stoney Trent, Jorn Kohlhammer, Graig Sauer, Robert Gove, Daniel Best, Celeste Lyn Paul, Nicolas Prigent, Diane Staheli |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781538681947 |
| DOIs | |
| State | Published - May 7 2019 |
| Externally published | Yes |
| Event | 2018 IEEE Symposium on Visualization for Cyber Security, VizSec 2018 - Berlin, Germany Duration: Oct 22 2018 → … |
Publication series
| Name | 2018 IEEE Symposium on Visualization for Cyber Security, VizSec 2018 |
|---|
Conference
| Conference | 2018 IEEE Symposium on Visualization for Cyber Security, VizSec 2018 |
|---|---|
| Country | Germany |
| City | Berlin |
| Period | 10/22/18 → … |
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Keywords
- Human-centered computing
- Visualization
- Visualization design and evaluation methods
ASJC Scopus subject areas
- Computer Science Applications
- Software
Cite this
An Empirical Study on Perceptually Masking Privacy in Graph Visualizations. / Chou, Jia Kai; Bryan, Chris; Li, Jing; Ma, Kwan Liu.
2018 IEEE Symposium on Visualization for Cyber Security, VizSec 2018. ed. / Stoney Trent; Jorn Kohlhammer; Graig Sauer; Robert Gove; Daniel Best; Celeste Lyn Paul; Nicolas Prigent; Diane Staheli. Institute of Electrical and Electronics Engineers Inc., 2019. 8709181 (2018 IEEE Symposium on Visualization for Cyber Security, VizSec 2018).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - An Empirical Study on Perceptually Masking Privacy in Graph Visualizations
AU - Chou, Jia Kai
AU - Bryan, Chris
AU - Li, Jing
AU - Ma, Kwan Liu
PY - 2019/5/7
Y1 - 2019/5/7
N2 - Researchers such as sociologists create visualizations of multivariate node-link diagrams to present findings about the relationships in communities. Unfortunately, such visualizations can inadvertently expose the ostensibly private identities of the persons that make up the dataset. By purposely violating graph readability metrics for a small region of the graph, we conjecture that local, exposed privacy leaks may be perceptually masked from easy recognition. In particular, we consider three commonly known metrics∗edge crossing, node clustering, and node-edge overlapping∗as a strategy to hide leaks. We evaluate the effectiveness of violating these metrics by conducting a user study that measures subject performance at visually searching for and identifying a privacy leak. Results show that when more masking operations are applied, participants needed more time to locate the privacy leak, though exhaustive, brute force search can eventually find it. We suggest future directions on how perceptual masking can be a viable strategy, primarily where modifying the underlying network structure is unfeasible.
AB - Researchers such as sociologists create visualizations of multivariate node-link diagrams to present findings about the relationships in communities. Unfortunately, such visualizations can inadvertently expose the ostensibly private identities of the persons that make up the dataset. By purposely violating graph readability metrics for a small region of the graph, we conjecture that local, exposed privacy leaks may be perceptually masked from easy recognition. In particular, we consider three commonly known metrics∗edge crossing, node clustering, and node-edge overlapping∗as a strategy to hide leaks. We evaluate the effectiveness of violating these metrics by conducting a user study that measures subject performance at visually searching for and identifying a privacy leak. Results show that when more masking operations are applied, participants needed more time to locate the privacy leak, though exhaustive, brute force search can eventually find it. We suggest future directions on how perceptual masking can be a viable strategy, primarily where modifying the underlying network structure is unfeasible.
KW - Human-centered computing
KW - Visualization
KW - Visualization design and evaluation methods
UR - http://www.scopus.com/inward/record.url?scp=85066411763&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85066411763&partnerID=8YFLogxK
U2 - 10.1109/VIZSEC.2018.8709181
DO - 10.1109/VIZSEC.2018.8709181
M3 - Conference contribution
AN - SCOPUS:85066411763
T3 - 2018 IEEE Symposium on Visualization for Cyber Security, VizSec 2018
BT - 2018 IEEE Symposium on Visualization for Cyber Security, VizSec 2018
A2 - Trent, Stoney
A2 - Kohlhammer, Jorn
A2 - Sauer, Graig
A2 - Gove, Robert
A2 - Best, Daniel
A2 - Paul, Celeste Lyn
A2 - Prigent, Nicolas
A2 - Staheli, Diane
PB - Institute of Electrical and Electronics Engineers Inc.
ER -